Provably Solving the Hidden Subset Sum Problem via Statistical Learning
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Keywords

cryptanalysis
lattice reduction
statistical attack
FastICA

How to Cite

Coron, J.-S., & Gini, A. (2022). Provably Solving the Hidden Subset Sum Problem via Statistical Learning. Mathematical Cryptology, 1(2), 70–84. Retrieved from https://journals.flvc.org/mathcryptology/article/view/130558

Abstract

At Crypto ’99, Nguyen and Stern described a lattice based algorithm for solving the hidden subset sum problem, a variant of the classical subset sum problem where the n weights are also hidden. As an application, they showed how to break the Boyko et al. fast generator of random pairs (x, gx (mod p)). The Nguyen-Stern algorithm works quite well in practice for moderate values of n, but its complexity is exponential in n. A polynomial-time variant was recently described at Crypto 2020, based on a multivariate technique, but the approach is heuristic only. In this paper, we describe a proven polynomial-time algorithm for solving the hidden subset-sum problem, based on statistical learning. In addition, we show that the statistical approach is also quite efficient in practice: using the FastICA algorithm, we can reach n = 250 in reasonable time.

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Copyright (c) 2022 Jean-Sébastien Coron, Agnese Gini